Results for “integration of the source function” — Page 28

NASA NTRS1998

Thermal State-of-Charge in Solar Heat Receivers

A theoretical framework is developed to determine the so-called thermal state-of-charge (SOC) in solar heat receivers employing encapsulated phase change materials (PCMS) that undergo cyclic melting and freezing. The present problem is relevant to space solar dynamic power systems that would typically operate in low-Earth-orbit (LEO). The solar heat receiver is integrated into a closed-cycle Brayton engine that produces electric power during sunlight and eclipse periods of the orbit cycle. The concepts of available power and virtual source temperature, both on a finite-time basis, are used as the basis for determining the SOC. Analytic expressions for the available power crossing the aperture plane of the receiver, available power stored in the receiver, and available power delivered to the working fluid are derived, all of which are related to the SOC through measurable parameters. Lower and upper bounds on the SOC are proposed in order to delineate absolute limiting cases for a range of input parameters (orbital, geometric, etc.). SOC characterization is also performed in the subcooled, two-phase, and superheat regimes. Finally, a previously-developed physical and numerical model of the solar heat receiver component of NASA Lewis Research Center's Ground Test Demonstration (GTD) system is used in order to predict the SOC as a function of measurable parameters.

Hall, Carsie, A., III↗

NASA NTRSDate not supplied

Innovative Features of NASA's Celestial Mapping System to Support Exploration in the Lunar South Pole

Introduction: NASA's Celestial Mapping System (CMS) is developed to address the need for 3D tools for planetary science investigations, mission planning, in-situ operations, in a 3D-first design constructed around a unified view of a planetary globe. At present CMS provides many critical functionalities that include 1) Equipment planning and optimized placement on Lunar surface 2) Line of sight (visibility ) analysis 3) Powerful measurement tools based on 3D terrain with realistic 3D models to represent rovers, astronauts and equipment 4) Visualization of de-rived mapping products (e.g. resource maps), and 5) Data engine for hosting new observations that are not available in other contemporary lunar data tools. CMS is built on the foundation of powerful NASA WorldWind globe engines. In near future, users will be able to simultaneously deploy CMS onto multiple hardware configurations and platforms such as Windows, Linux, iOS and Android. The users will also have the flexibility to update to the latest imagery and terrain datasets as they are being acquired (in real time) before and/or during the exploration mission. CMS is also capable of consumption and analysis of data from locally hosted and external sources. It supports Open Geospatial Consorti-um (OGC) data and file standards, with current integrations of datasets from the Astrogeology Science Center of USGS which include global and local data acquired from NASA (LRO, Clementine, Lunar Orbiter) and JAXA (SELENE/Kaguya) with the capability of integrating more datasets. With development experience in both the end-user application and planetary engine side, CMS is also able to adapt to newer Lunar cartography standards as they develop and become recognized by international geospatial panels. Overcoming Polar Distortions: 3D geospatial applications traditionally suffer from significant distortion of imagery at the poles due to following reasons – 1) distortions in the source imagery 2) Incompatible tessellation algorithm on the poles 3) map projections. In the lunar context, with the focus on the South pole, this is not acceptable. The CMS team is researching ways to address polar distortion of imagery with new tessellation algorithms and by reprojecting the data using projections that are more accurate in polar scenarios. Figure1 shows the potential error introduced by different tessellation methods, represented by the red and green circles for Shoemaker crater. There is ~2 Km difference in the placement of the crater. Line of Sight Analysis and Traverse Planning: We have developed a built-in line of sight analysis (LOS) tool in CMS that analyzes the terrain profile and obstructions and provides the visibility of a given terrain for a remote observer. Figure 2 shows the viewshed analysis on the PSR in Nobile region. The PSR was created with help of HORUS generated images. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. This analysis was ex-tended further to set different heights for various observers and then perform the viewshed analysis. Combining the different visibility profiles can help designing improved traverses within the crater.

Geospatial Mapping↗

NASA NTRSDate not supplied

Innovative Features of NASA's Celestial Mapping System to Support Exploration in the Lunar South Pole

Introduction: NASA's Celestial Mapping System (CMS) is developed to address the need for 3D tools for planetary science investigations, mission planning, in-situ operations, in a 3D-first design constructed around a unified view of a planetary globe. At present CMS provides many critical functionalities that include 1) Equipment planning and optimized placement on Lunar surface 2) Line of sight (visibility ) analysis 3) Powerful measurement tools based on 3D terrain with realistic 3D models to represent rovers, astronauts and equipment 4) Visualization of de-rived mapping products (e.g. resource maps), and 5) Data engine for hosting new observations that are not available in other contemporary lunar data tools. CMS is built on the foundation of powerful NASA WorldWind globe engines. In near future, users will be able to simultaneously deploy CMS onto multiple hardware configurations and platforms such as Windows, Linux, iOS and Android. The users will also have the flexibility to update to the latest imagery and terrain datasets as they are being acquired (in real time) before and/or during the exploration mission. CMS is also capable of consumption and analysis of data from locally hosted and external sources. It supports Open Geospatial Consorti-um (OGC) data and file standards, with current integrations of datasets from the Astrogeology Science Center of USGS which include global and local data acquired from NASA (LRO, Clementine, Lunar Orbiter) and JAXA (SELENE/Kaguya) with the capability of integrating more datasets. With development experience in both the end-user application and planetary engine side, CMS is also able to adapt to newer Lunar cartography standards as they develop and become recognized by international geospatial panels. Overcoming Polar Distortions: 3D geospatial applications traditionally suffer from significant distortion of imagery at the poles due to following reasons – 1) distortions in the source imagery 2) Incompatible tessellation algorithm on the poles 3) map projections. In the lunar context, with the focus on the South pole, this is not acceptable. The CMS team is researching ways to address polar distortion of imagery with new tessellation algorithms and by reprojecting the data using projections that are more accurate in polar scenarios. Figure1 shows the potential error introduced by different tessellation methods, represented by the red and green circles for Shoemaker crater. There is ~2 Km difference in the placement of the crater. Line of Sight Analysis and Traverse Planning: We have developed a built-in line of sight analysis (LOS) tool in CMS that analyzes the terrain profile and obstructions and provides the visibility of a given terrain for a remote observer. Figure 2 shows the viewshed analysis on the PSR in Nobile region. The PSR was created with help of HORUS generated images. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. This analysis was ex-tended further to set different heights for various observers and then perform the viewshed analysis. Combining the different visibility profiles can help designing improved traverses within the crater.

Geospatial Mapping↗

NASA NTRS2014

Human Exploration Science Office (KX) Overview

The Human Exploration Science Office supports human spaceflight, conducts research, and develops technology in the areas of space orbital debris, hypervelocity impact technology, image science and analysis, remote sensing, imagery integration, and human and robotic exploration science. NASA's Orbital Debris Program Office (ODPO) resides in the Human Exploration Science Office. ODPO provides leadership in orbital debris research and the development of national and international space policy on orbital debris. The office is recognized internationally for its measurement and modeling of the debris environment. It takes the lead in developing technical consensus across U.S. agencies and other space agencies on debris mitigation measures to protect users of the orbital environment. The Hypervelocity Impact Technology (HVIT) project evaluates the risks to spacecraft posed by micrometeoroid and orbital debris (MMOD). HVIT facilities at JSC and White Sands Test Facility (WSTF) use light gas guns, diagnostic tools, and high-speed imagery to quantify the response of spacecraft materials to MMOD impacts. Impact tests, with debris environment data provided by ODPO, are used by HVIT to predict risks to NASA and commercial spacecraft. HVIT directly serves NASA crew safety with MMOD risk assessments for each crewed mission and research into advanced shielding design for future missions. The Image Science and Analysis Group (ISAG) supports the International Space Station (ISS) and commercial spaceflight through the design of imagery acquisition schemes (ground- and vehicle-based) and imagery analyses for vehicle performance assessments and mission anomaly resolution. ISAG assists the Multi-Purpose Crew Vehicle (MPCV) Program in the development of camera systems for the Orion spacecraft that will serve as data sources for flight test objectives that lead to crewed missions. The multi-center Imagery Integration Team is led by the Human Exploration Science Office and provides expertise in the application of engineering imagery to spaceflight. The team links NASA programs and private industry with imagery capabilities developed and honed through decades of human spaceflight, including imagery integration, imaging assets, imagery data management, and photogrammetric analysis. The team is currently supporting several NASA programs, including commercial demonstration missions. The Earth Science and Remote Sensing Team is responsible for integrating the scientific use of Earth-observation assets onboard the ISS, which consist of externally mounted sensors and crew photography capabilities. This team facilitates collaboration on remote sensing and participates in research with academic organizations and other Government agencies, not only in conjunction with ISS science, but also for planetary exploration and regional environmental/geological studies. Human exploration science focuses on science strategies for future human exploration missions to the Moon, Mars, asteroids, and beyond. This function provides communication and coordination between the science community and mission planners. ARES scientists support the operation of robotic missions (i.e., Mars Exploration Rovers and the Mars Science Laboratory), contribute to the interpretation of returned mission data, and translate robotic mission technologies and techniques to human spaceflight.

Calhoun, Tracy A.↗

NASA NTRS1991

Some practical universal noiseless coding techniques, part 3, module PSl14,K+

The algorithmic definitions, performance characterizations, and application notes for a high-performance adaptive noiseless coding module are provided. Subsets of these algorithms are currently under development in custom very large scale integration (VLSI) at three NASA centers. The generality of coding algorithms recently reported is extended. The module incorporates a powerful adaptive noiseless coder for Standard Data Sources (i.e., sources whose symbols can be represented by uncorrelated non-negative integers, where smaller integers are more likely than the larger ones). Coders can be specified to provide performance close to the data entropy over any desired dynamic range (of entropy) above 0.75 bit/sample. This is accomplished by adaptively choosing the best of many efficient variable-length coding options to use on each short block of data (e.g., 16 samples) All code options used for entropies above 1.5 bits/sample are 'Huffman Equivalent', but they require no table lookups to implement. The coding can be performed directly on data that have been preprocessed to exhibit the characteristics of a standard source. Alternatively, a built-in predictive preprocessor can be used where applicable. This built-in preprocessor includes the familiar 1-D predictor followed by a function that maps the prediction error sequences into the desired standard form. Additionally, an external prediction can be substituted if desired. A broad range of issues dealing with the interface between the coding module and the data systems it might serve are further addressed. These issues include: multidimensional prediction, archival access, sensor noise, rate control, code rate improvements outside the module, and the optimality of certain internal code options.

Rice, Robert F.↗

NASA NTRS1998

X-33 Integrated Test facility, Extended Range Simulation

In support of the X-33 Single Stage To Orbit program, NASA Dryden Flight Research Center was selected to provide continuous communications coverage of the X-33 vehicle from launch, through landing at Malmstrom Air Force Base, Montana and Michaels Army Air Field, Utah. An extensive real-time range simulation capability is being developed to ensure successful communications with the autonomous X-33 vehicle. This paper will provide an overview of the various levels of simulation being developed to support the X-33 extended range subsystems. These subsystems include the Flight Termination System, L-Band command uplink subsystem and the S-Band telemetry downlink subsystem. In addition, the radar model developed provides continuous azimuth, elevation and range information based on the flight trajectory. The Dynamic Ground Station Analysis model developed by NASA Goddard Space Flight Center, calculate the received signal strength at each ground station. This model takes into consideration Radio Frequency (RF) link parameters such as frequency, antenna gain, space loss, plasma effects and the vehicle's position and attitude at any point in time during the flight path. All three RF links are then attenuated based on this calculated level and the RF signals are sent into telemetry receivers to emulate remote sites, or the power incident on the vehicle from uplinked signals. The best source received telemetry data is then passed back to the Launch and Mission Control Monitoring System (LMCMS) resident in the Operations Control Center. The LMCMS also provides the range simulation system the uplink command combined with differential GPS corrections. Later stages will require the progressive integration of actual range hardware with this simulation effort, leading to communication between telemetry, uplink and FTS antennas at NASA Dryden Flight Research Center, with vehicle antennas mounted on the Walter C. Williams Research Aircraft Integration Facility (RAIF). Decommutated Pulse Code Modulated (PCM) data is displayed on one of the four monitors that comprise the Range Safety Officer's (RSO) station. Also displayed are instantaneous impact prediction models, and Federal Aviation Administration (FAA) data for notification of other traffic in the area. Aside from initiating the flight termination command and validating communication links, the RSO station with the range simulation will be used to provide both range control and range safety officers training. The training is necessary to perform their respective functions with greater levels of confidence prior to first flight.

Sharma, Ashley↗

NASA NTRSDate not supplied

Towards Energy Scale Calibration and Drift Correction of TES Detectors for Athena X-IFU

The Athena X-Ray Integral Field Unit (X-IFU) comprises a 2376-pixel array of transition edge sensors (TES) read out with time-division multiplexing (TDM). X-IFU will provide spatially resolved, high-resolution spectroscopy (2.5 eV full-width-half-maximum up to 7 keV) over the energy range 0.2 to 12 keV, with an absolute energy scale accuracy of 0.4 eV. The energy scale function maps the optimally filtered pulse height, in arbitrary engineering units, to real calibrated energy. Uncertainties in the calibration can result from imperfect fitting of the energy scale between the known calibration points. Furthermore, temporal changes in the TES operating environment, such as heat-sink temperature, magnetic field and bias voltage, can cause significant variations in the detector gain function over time. If not properly corrected, this can result in degradation of the energy resolution, and systematic errors in the absolute energy scale. The non-linear nature of TES detectors, coupled with the possibility of multiple simultaneously occurring sources of drift, can make effective corrections over the full bandpass of the instrument extremely challenging. Athena X-IFU will employ an on-board calibration source that provides known reference x-ray lines. This provides real-time monitoring of the gain stability of the detector system and information that can be used to correct for gain drifts. For X-IFU the baseline approach is to measure a series of calibration curves under different environmental conditions, which bound the expected drifts the instrument is predicted to see over the course of the mission. Using the information from the in-flight calibration source, these energy scale functions can be interpolated to generate a new corrected energy scale as a function of time. In this paper we discuss progress towards demonstrating that the X-IFU energy scale requirements can be met. We present measurements on ~ 200 pixels in a prototype X-IFU array read out with 8-column x 32-row TDM. We use a rotating target source containing 12 fluorescent targets to generate x-ray lines covering the energy range 4 keV (Sc-Kα) to 12 keV (Br-Kα). We present measurements of the non-linear energy scale function and show how variations in heat-sink temperature, TES bias voltage and magnetic field affect the shape of TES energy scale differently and introduce different residual gain errors over the bandpass. We explore different drift correction algorithms that use either a single or multiple referential lines to track and correct the gain from these various sources of drift. In addition to the pulse-height, the DC ‘baseline’ level of the TES can contain information about its bias conditions. Thus, we test a multi-parameter gain correction algorithm that attempts to incorporate both the pulse height and the additional baseline information into the algorithm.

Stephen J Smith↗

NASA NTRS1995

Morphology, near-infrared luminosity, and mass of the Galactic bulge from COBE DIRBE observations

Near-infrared images of the Galactic bulge at 1.25, 2.2, 3.5, and 4.9 microns obtained by the Diffuse Infrared Background Experiment (DIRBE) onboard the Cosmic Background Explorer (COBE) satellite are used to characterize its morphology and to determine its infrared luminosity and mass. Earlier analysis of the DIRBE observations (Weiland et al. 1994) provided supporting evidence for the claim made by Blitz & Spergel (1991) that the bulge is bar-shaped with its near end in the first Galactic quadrant. Adopting various triaxial analytical functions to represent the volume emissivity of the source, we confirm the barlike nature of the bulge and show that triaxial Gaussian-type functions provide a better fit to the data than other classes of functions, including an axisymmetric spheroid. The introduction of a `boxy' geometry, such as the one used by Kent, Dame, & Fazio (1991) improves the fit to the data. Our results show that the bar is rotated in the plane with its near side in the first Galactic quadrant creating an angle of 20 deg +/- 10 deg between its major axis and the line of sight to the Galactic center. Typical axis ratios of the bar are (1:0.33 +/- 0.11:0.23 +/- 0.08), resembling the geometry of prolate spheroids. There is no statistically significant evidence for an out-of-plane tilt of the bar at 2.2 microns, and marginal evidence for a tilt of approximately equal 2 deg at 4.9 microns. The introduction of a roll around the intrinsic major axis of the bulge improves the `boxy' appearance of some functions. A simple integration of the observed projected intensity of the bulge gives a bulge luminosity of 1.2 x 10(exp 9), 4.1 x 10(exp 8), 2.3 x 10(exp 8), and 4.3 x 10(exp 7) solar luminosity, respectively, at 1.25, 2.2, 3.5, and 4.9 microns wavelength for a Galactocentric distance of 8.5 kpc. The 2.2 microns luminosity function of the bulge population in the direction of Baade's window yields a bolometric luminosity of L(sub bol) = 5.3 x 10(exp 9) solar luminosity. Stellar evolutionary models relate this luminosity to the number of main-sequence progenitor stars that currently populate the red giant branch. Combined with the recent determination of the main-sequence turnoff mass for the bulge by the Hubble Space Telescope (Holtzman et al. 1993) we derive a photometrically determined bulge mass of approximately equal to 1.3 x 10(exp 10) solar mass for a Salpeter initial mass function extended down to 0.1 solar mass.

Dwek, E.↗

NASA NTRS2015

Characterization of Flap Edge Noise Radiation from a High-Fidelity Airframe Model

The results of an experimental study of the noise generated by a baseline high-fidelity airframe model are presented. The test campaign was conducted in the open-jet test section of the NASA Langley 14- by 22-foot Subsonic Tunnel on an 18%-scale, semi-span Gulfstream airframe model incorporating a trailing edge flap and main landing gear. Unsteady surface pressure measurements were obtained from a series of sensors positioned along the two flap edges, and far field acoustic measurements were obtained using a 97-microphone phased array that viewed the pressure side of the airframe. The DAMAS array deconvolution method was employed to determine the locations and strengths of relevant noise sources in the vicinity of the flap edges and the landing gear. A Coherent Output Power (COP) spectral method was used to couple the unsteady surface pressures measured along the flap edges with the phased array output. The results indicate that outboard flap edge noise is dominated by the flap bulb seal cavity with very strong COP coherence over an approximate model-scale frequency range of 1 to 5 kHz observed between the array output and those unsteady pressure sensors nearest the aft end of the cavity. An examination of experimental COP spectra for the inboard flap proved inconclusive, most likely due to a combination of coherence loss caused by decorrelation of acoustic waves propagating through the thick wind tunnel shear layer and contamination of the spectra by tunnel background noise at lower frequencies. Directivity measurements obtained from integration of DAMAS pressure-squared values over defined geometric zones around the model show that the baseline flap and landing gear are only moderately directional as a function of polar emission angle.

Humphreys, William M., Jr.↗

NASA NTRS2010

NASA Tech Briefs, July 2010

Topics covered include: Wirelessly Interrogated Wear or Temperature Sensors; Processing Nanostructured Sensors Using Microfabrication Techniques; Optical Pointing Sensor; Radio-Frequency Tank Eigenmode Sensor for Propellant Quantity Gauging; High-Temperature Optical Sensor; Integral Battery Power Limiting Circuit for Intrinsically Safe Applications; Configurable Multi-Purpose Processor; Squeezing Alters Frequency Tuning of WGM Optical Resonator; Automated Computer Access Request System; Range Safety for an Autonomous Flight Safety System; Fast and Easy Searching of Files in Unisys 2200 Computers; Parachute Drag Model; Evolutionary Scheduler for the Deep Space Network; Modular Habitats Comprising Rigid and Inflatable Modules; More About N2O-Based Propulsion and Breathable-Gas Systems; Ultrasonic/Sonic Rotary-Hammer Drills; Miniature Piezoelectric Shaker for Distribution of Unconsolidated Samples to Instrument Cells; Lunar Soil Particle Separator; Advanced Aerobots for Scientific Exploration; Miniature Bioreactor System for Long-Term Cell Culture; Electrochemical Detection of Multiple Bioprocess Analytes; Fabrication and Modification of Nanoporous Silicon Particles; High-Altitude Hydration System; Photon Counting Using Edge-Detection Algorithm; Holographic Vortex Coronagraph; Optical Structural Health Monitoring Device; Fuel-Cell Power Source Based on Onboard Rocket Propellants; Polar Lunar Regions: Exploiting Natural and Augmented Thermal Environments; Simultaneous Spectral Temporal Adaptive Raman Spectrometer - SSTARS; Improved Speed and Functionality of a 580-GHz Imaging Radar; Bolometric Device Based on Fluxoid Quantization; Algorithms for Learning Preferences for Sets of Objects; Model for Simulating a Spiral Software-Development Process; Algorithm That Synthesizes Other Algorithms for Hashing; Algorithms for High-Speed Noninvasive Eye-Tracking System; and Adapting ASPEN for Orbital Express.

Source record↗

NASA NTRS2003

164-GHz MMIC HEMT Frequency Doubler

A monolithic microwave integrated circuit (MMIC) that includes a high-electron-mobility transistor (HEMT) has been developed as a prototype of improved frequency doublers for generating signals at frequencies greater than 100 GHz. Signal sources that operate in this frequency range are needed for a variety of applications, notably including general radiometry and, more specifically, radiometric remote sensing of the atmosphere. Heretofore, it has been common practice to use passive (diode-based) frequency multipliers to obtain frequencies greater than 100 GHz. Unfortunately, diode-based frequency multipliers are plagued by high DC power consumption and low conversion efficiency. Moreover, multiplier diodes are not easily integrated with such other multiplier-circuit components as amplifiers and oscillators. The goals of developing the present MMIC HEMT frequency doubler were (1) to utilize the HEMT as an amplifier to increase conversion efficiency (more precisely, to reduce conversion loss), thereby increasing the output power for a given DC power consumption or, equivalently, reducing the DC power consumption for a given output power; and (2) to provide for the integration of amplifier and oscillator components on the same chip. The MMIC frequency doubler (see Figure 1) contains an AlInAs/GaInAs/InP HEMT biased at pinch-off to make it function as a class-B amplifier (meaning that it conducts in half-cycle pulses). Grounded coplanar waveguides (GCPWs) are used as impedance-matching transmission lines. Air bridges are placed at discontinuities to suppress undesired slot electromagnetic modes. Another combination of GCPWs also serves both as a low-pass filter to suppress undesired oscillations at frequencies below 60 GHz and as a DC blocker. Large decoupling capacitors and epitaxial resistors are added in the drain and gate lines to suppress bias oscillations. At the output terminal, the fundamental frequency is suppressed by a quarter-wave open stub, which presents a short circuit at the fundamental frequency and an open circuit at the second harmonic. At an input power of 7 mW, the output power and conversion loss at an output frequency of 164 GHz were found to be 5 dBm (approximately equal to 3.2 mW) and 2 dB, respectively, with a 3-dB output-power bandwidth of 14 GHz. This is the best performance reported to date for an MMIC HEMT frequency doubler above 100 GHz.

Samoska, Lorene↗

NASA NTRS2014

Analytical Assessment of Simultaneous Parallel Approach Feasibility from Total System Error

In a simultaneous paired approach to closely-spaced parallel runways, a pair of aircraft flies in close proximity on parallel approach paths. The aircraft pair must maintain a longitudinal separation within a range that avoids wake encounters and, if one of the aircraft blunders, avoids collision. Wake avoidance defines the rear gate of the longitudinal separation. The lead aircraft generates a wake vortex that, with the aid of crosswinds, can travel laterally onto the path of the trail aircraft. As runway separation decreases, the wake has less distance to traverse to reach the path of the trail aircraft. The total system error of each aircraft further reduces this distance. The total system error is often modeled as a probability distribution function. Therefore, Monte-Carlo simulations are a favored tool for assessing a "safe" rear-gate. However, safety for paired approaches typically requires that a catastrophic wake encounter be a rare one-in-a-billion event during normal operation. Using a Monte-Carlo simulation to assert this event rarity with confidence requires a massive number of runs. Such large runs do not lend themselves to rapid turn-around during the early stages of investigation when the goal is to eliminate the infeasible regions of the solution space and to perform trades among the independent variables in the operational concept. One can employ statistical analysis using simplified models more efficiently to narrow the solution space and identify promising trades for more in-depth investigation using Monte-Carlo simulations. These simple, analytical models not only have to address the uncertainty of the total system error but also the uncertainty in navigation sources used to alert an abort of the procedure. This paper presents a method for integrating total system error, procedure abort rates, avionics failures, and surveillance errors into a statistical analysis that identifies the likely feasible runway separations for simultaneous paired approaches.

Madden, Michael M.↗

NASA NTRS2024

Evaluating Liftoff Debris for NASA’s Space Launch System (SLS) Prior to the Artemis I Launch

The SLS Artemis I launch vehicle is the first of several planned Artemis launch vehicles, with a number of design differences from earlier NASA missions that incur liftoff debris risk to the mission. As a test vehicle, the Artemis I hardware also endured environments and tests not planned for future missions, which led to several additional factors contributing to an evolving liftoff debris risk to the SLS vehicle. This paper will summarize these risk factors and address the processes used to evaluate and communicate the risks to support a successful Artemis I launch. It will discuss how the evolving risks that were quantified and evaluated by a Cross-Program team of debris Subject Matter Experts to mitigate liftoff debris hazards and communicate updated risk to the SLS vehicle. This process was performed through the inaugural use of an SLS debris day-of-launch (DOL) standard operating procedure that will be used for subsequent Artemis missions. This paper addresses the risk of liftoff debris, debris released by the vehicle or from the launch pad during liftoff through vehicle tower clear. Expected liftoff debris is well understood from previous NASA programs’ experience and from tests of materials, processes and functions that are known to release liftoff debris. These expected sources were assessed and cleared well ahead of launch day. However, given the ever-changing schedules and environments, processes were in place to evaluate any additional potential liftoff debris risks identified during launch countdown. Although many of the Artemis vehicle hardware components are similar to those on the NASA Shuttle Program, there are important differences in the architecture of the Artemis I vehicle which require new assessments of liftoff debris risk for the Artemis missions. The more favorable Artemis crew module location and surfaces are far less vulnerable to debris impacts; however, the longer vehicle can result in higher liftoff debris impact energies to those components on the aft end of the vehicle. Additionally, the positional change of the RS-25 liquid engines to nearer the Booster nozzle exit plane along with the change in Booster throat plug design is a disadvantage to the overall liftoff debris risk which resulted in additional test and analysis efforts for evaluating the integrated vehicle debris risk. In spite of the comprehensive tests and analyses of Artemis I expected liftoff debris, a number of additional tests/processes were completed prior to the Artemis I mission that were required to support a complete understanding of a new launch vehicle, but increased the risk of releasing liftoff debris. The hardware endured several additional cryogenic loading cycles, including the Green Run tests at Stennis Space Center, Wet Dress Rehearsals at Kennedy Space Center, and multiple launch attempts. Each of these cycles induced stresses in the thermal protection system (TPS) materials, increasing the risk of damage to and release of the TPS. Additionally, induced and weather environmental factors that could increase the likelihood of debris release were significant. Vibrations and stresses in the TPS were induced by a required roll-back to the Vehicle Assembly Building before Hurricane Ian to protect the vehicle from damage by high winds. Wind damage and potential internal stresses to several outer mold line materials on the integrated SLS vehicle and mobile launcher were caused by weathering Hurricane Nicole at Pad 39B the week before launch. A thorough imagery scan of the vehicle was performed after each event and the damage observed was repaired, removed, or assessed and the risk to the mission evaluated. Mitigation of debris risk can occur by tests and analyses to show debris impacted components as damage tolerant, by new/improved processes for prevention of debris availability, or redesign. Risk mitigation processes for Artemis I-specific liftoff debris events and the development and use of the SLS debris day of launch (DOL) procedures that will be used for subsequent Artemis missions will be described.

Space Launch System↗

NASA NTRSDate not supplied

Evaluating Liftoff Debris for NASA’s Space Launch System (SLS) Prior to the Artemis I Launch

The SLS Artemis I launch vehicle is the first of several planned Artemis launch vehicles, with a number of design differences from earlier NASA missions that incur liftoff debris risk to the mission. As a test vehicle, the Artemis I hardware also endured environments and tests not planned for future missions, which led to several additional factors contributing to an evolving liftoff debris risk to the SLS vehicle. This paper will summarize these risk factors and address the processes used to evaluate and communicate the risks to support a successful Artemis I launch. It will discuss how the evolving risks that were quantified and evaluated by a Cross-Program team of debris Subject Matter Experts to mitigate liftoff debris hazards and communicate updated risk to the SLS vehicle. This process was performed through the inaugural use of an SLS debris day-of-launch (DOL) standard operating procedure that will be used for subsequent Artemis missions. This paper addresses the risk of liftoff debris, debris released by the vehicle or from the launch pad during liftoff through vehicle tower clear. Expected liftoff debris is well understood from previous NASA programs’ experience and from tests of materials, processes and functions that are known to release liftoff debris. These expected sources were assessed and cleared well ahead of launch day. However, given the ever-changing schedules and environments, processes were in place to evaluate any additional potential liftoff debris risks identified during launch countdown. Although many of the Artemis vehicle hardware components are similar to those on the NASA Shuttle Program, there are important differences in the architecture of the Artemis I vehicle which require new assessments of liftoff debris risk for the Artemis missions. The more favorable Artemis crew module location and surfaces are far less vulnerable to debris impacts; however, the longer vehicle can result in higher liftoff debris impact energies to those components on the aft end of the vehicle. Additionally, the positional change of the RS-25 liquid engines to nearer the Booster nozzle exit plane along with the change in Booster throat plug design is a disadvantage to the overall liftoff debris risk which resulted in additional test and analysis efforts for evaluating the integrated vehicle debris risk. In spite of the comprehensive tests and analyses of Artemis I expected liftoff debris, a number of additional tests/processes were completed prior to the Artemis I mission that were required to support a complete understanding of a new launch vehicle, but increased the risk of releasing liftoff debris. The hardware endured several additional cryogenic loading cycles, including the Green Run tests at Stennis Space Center, Wet Dress Rehearsals at Kennedy Space Center, and multiple launch attempts. Each of these cycles induced stresses in the thermal protection system (TPS) materials, increasing the risk of damage to and release of the TPS. Additionally, induced and weather environmental factors that could increase the likelihood of debris release were significant. Vibrations and stresses in the TPS were induced by a required roll-back to the Vehicle Assembly Building before Hurricane Ian to protect the vehicle from damage by high winds. Wind damage and potential internal stresses to several outer mold line materials on the integrated SLS vehicle and mobile launcher were caused by weathering Hurricane Nicole at Pad 39B the week before launch. A thorough imagery scan of the vehicle was performed after each event and the damage observed was repaired, removed, or assessed and the risk to the mission evaluated. Mitigation of debris risk can occur by tests and analyses to show debris impacted components as damage tolerant, by new/improved processes for prevention of debris availability, or redesign. Risk mitigation processes for Artemis I-specific liftoff debris events and the development and use of the SLS debris day of launch (DOL) procedures that will be used for subsequent Artemis missions will be described.

Space Launch System↗

NASA NTRS2002

Fan Noise Source Diagnostic Test: Vane Unsteady Pressure Results

To investigate the nature of fan outlet guide vane pressure fluctuations and their link to rotor-stator interaction noise, time histories of vane fluctuating pressures were digitally acquired as part of the Fan Noise Source Diagnostic Test. Vane unsteady pressures were measured at seven fan tip speeds for both a radial and a swept vane configuration. Using time-domain averaging and spectral analysis, the blade passing frequency (BPF) harmonic and broadband contents of the vane pressures were individually analyzed. Significant Sound Pressure Level (SPL) reductions were observed for the swept vane relative to the radial vane for the BPF harmonics of vane pressure, but vane broadband reductions due to sweep turned out to be much smaller especially on an average basis. Cross-correlation analysis was used to establish the level of spatial coherence of broadband pressures between different locations on the vane and integral length scales of pressure fluctuations were estimated from these correlations. Two main results of this work are: (1) the average broadband level on the vane (in dB) increases linearly with the fan tip speed for both the radial and swept vanes, and (2) the broadband pressure distribution on the vane is nearly homogeneous and its integral length scale is a monotonically decreasing function of fan tip speed.

Envia, Edmane↗

NASA NTRS2010

Optical Imaging and Radiometric Modeling and Simulation

OPTOOL software is a general-purpose optical systems analysis tool that was developed to offer a solution to problems associated with computational programs written for the James Webb Space Telescope optical system. It integrates existing routines into coherent processes, and provides a structure with reusable capabilities that allow additional processes to be quickly developed and integrated. It has an extensive graphical user interface, which makes the tool more intuitive and friendly. OPTOOL is implemented using MATLAB with a Fourier optics-based approach for point spread function (PSF) calculations. It features parametric and Monte Carlo simulation capabilities, and uses a direct integration calculation to permit high spatial sampling of the PSF. Exit pupil optical path difference (OPD) maps can be generated using combinations of Zernike polynomials or shaped power spectral densities. The graphical user interface allows rapid creation of arbitrary pupil geometries, and entry of all other modeling parameters to support basic imaging and radiometric analyses. OPTOOL provides the capability to generate wavefront-error (WFE) maps for arbitrary grid sizes. These maps are 2D arrays containing digital sampled versions of functions ranging from Zernike polynomials to combination of sinusoidal wave functions in 2D, to functions generated from a spatial frequency power spectral distribution (PSD). It also can generate optical transfer functions (OTFs), which are incorporated into the PSF calculation. The user can specify radiometrics for the target and sky background, and key performance parameters for the instrument s focal plane array (FPA). This radiometric and detector model setup is fairly extensive, and includes parameters such as zodiacal background, thermal emission noise, read noise, and dark current. The setup also includes target spectral energy distribution as a function of wavelength for polychromatic sources, detector pixel size, and the FPA s charge diffusion modulation transfer function (MTF).

Ha, Kong Q.↗

NASA NTRSDate not supplied

Developing Concepts of Operations Using Multi-Step Tool Techniques With Large Language Models

The National Aeronautics and Space Administration (NASA) Air Mobility Pathfinders (AMP) project is developing and evaluating concepts of operations (ConOps) for safe, secure, and scalable Urban Air Mobility (UAM) operations. The AMP project’s Operational Concepts, Architecture, and Requirements Integration (OCARI) Team is using a Model Based System Engineering (MBSE) approach for integration, interoperability, and traceability of Advanced Air Mobility (AAM) ecosystems centered around urban air taxi services. The team’s goal is to define structures and behaviors needed for system feasibility, readiness, and interoperability, establish a UAM knowledge base, and trace and validate assumptions and requirements relevant to AAM. NASA Langley Research Center (LaRC) is spearheading an innovative digital engineering approach to integrate, communicate, and facilitate the research of multi-modal transportation systems. The Knowledge-based Digital Platform (KbDP) is a concept being developed that ties the workflows of Project Managers (PM), Principal Investigators (PI), and System Engineers together across organizational boundaries. It does so through the management of an information database defined by mathematical, data science, and system engineering principles. Machine Learning (ML) algorithms play a key role in this concept by extracting meaningful knowledge from relational and graph databases, document repositories, and system artifacts, which the human user leverages to greatly improve the efficiency and effectiveness of their research. Recent advancements in the field of Large Language Models (LLMs), specifically models trained for tool use, such as Command-R , now allow for the reliable implementation of single-step and multi-step tool-centric systems. These techniques provide the LLM with a set of tools, in our case Python functions, that can be called on to answer a much wider range of questions compared to LLMs implemented using a traditional single-source or Retrieval Augmented Generation (RAG) approach. Through this method, the LLM can pull information from multiple data sources, such as relational or graph databases, document repositories, application programming interfaces (APIs), and SysML artifacts depending on the user’s question. The LLM can also output the information in a variety of different formats, using output generation tools, such as CSV, UML, or SysML artifacts. Additionally, tools can be assigned roles and can work together to provide answers to queries in an “agent” like approach, similar to that implemented by Microsoft’s AutoGen framework where different agents can converse with each other to accomplish tasks. Previously, our team developed a chatbot system with “agent like” functionality in the form of different “modes” the user could select from a user interface (UI), this architecture can be seen on the left in figure 1. Three different modes were implemented, the first mode allowed the LLM to utilize the structures and algorithms within a graph database to trace UAM requirements. The second mode gave the LLM access to a vector search capable of providing relevant information from thousands of document pages related to UAM ConOps and requirements. The third mode served as a general assistant where users could enter open-ended questions and custom prompts to utilize the LLM for different use-cases. This system improved the process surrounding generating and analyzing information related to UAM requirements, however, the implementation provided a clunky user experience. Users were required to know what mode to select within the UI in advance before entering their question to the selected tool. Moreover, the different tools were isolated from each other, they lacked bidirectional links that would allow for tools to collaborate to generate better responses. Our team is working on a new architecture, seen on the right in the below figure, with the goal to address many of the UX shortcomings of our original system while improving the accuracy and depth of responses from the LLM. This new system will automatically select the appropriate tool to use based off the user’s question. Each tool will be capable of calling on any of the other tools available to the LLM, resulting in a collaborative pipeline where tools can pass data between other tools until enough data is received to generate an answer to the user’s question. Using a locally deployed, open-source, LLM, the NASA OCARI team, in collaboration with Collins Aerospace, will implement a prototype application that will bridge knowledge across multiple sources to assist System Engineers (SEs) with requirements discovery and tracing, research question and use case identification, and assumption validation. Such a system will also allow SEs to more easily, and intuitively, explore the AAM ecosystem, ultimately improving the efficiency and effectiveness of the SE's research and decision-making processes surrounding ConOps development and validation. In this session, our team will provide a video demonstration of our new prototype architecture in action. We will also present an overview of our prototype system architecture and talk about its advantages over traditional LLM deployments along with how those advantages can provide additional value to the field of System Engineering.

systems engineering↗

NASA NTRS2016

Recent Progresses in Incorporating Human Land-Water Management into Global Land Surface Models Toward Their Integration into Earth System Models

The global water cycle has been profoundly affected by human land-water management. As the changes in the water cycle on land can affect the functioning of a wide range of biophysical and biogeochemical processes of the Earth system, it is essential to represent human land-water management in Earth system models (ESMs). During the recent past, noteworthy progress has been made in large-scale modeling of human impacts on the water cycle but sufficient advancements have not yet been made in integrating the newly developed schemes into ESMs. This study reviews the progresses made in incorporating human factors in large-scale hydrological models and their integration into ESMs. The study focuses primarily on the recent advancements and existing challenges in incorporating human impacts in global land surface models (LSMs) as a way forward to the development of ESMs with humans as integral components, but a brief review of global hydrological models (GHMs) is also provided. The study begins with the general overview of human impacts on the water cycle. Then, the algorithms currently employed to represent irrigation, reservoir operation, and groundwater pumping are discussed. Next, methodological deficiencies in current modeling approaches and existing challenges are identified. Furthermore, light is shed on the sources of uncertainties associated with model parameterizations, grid resolution, and datasets used for forcing and validation. Finally, representing human land-water management in LSMs is highlighted as an important research direction toward developing integrated models using ESM frameworks for the holistic study of human-water interactions within the Earths system.

biogeochemistry↗